AIMC Topic: Stochastic Processes

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State bounding for fuzzy memristive neural networks with bounded input disturbances.

Neural networks : the official journal of the International Neural Network Society Dec 3, 2020
This paper investigates the state bounding problem of fuzzy memristive neural networks (FMNNs) with bounded input disturbances. By using the characters of Metzler, Hurwitz and nonnegative matrices, this paper obtains the exact delay-independent and d...
Fuzzy Logic Stochastic Processes Neural Networks, Computer Algorithms
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Robust Stability Analysis of Delayed Stochastic Neural Networks via Wirtinger-Based Integral Inequality.

Neural computation Nov 30, 2020
We discuss stability analysis for uncertain stochastic neural networks (SNNs) with time delay in this letter. By constructing a suitable Lyapunov-Krasovskii functional (LKF) and utilizing Wirtinger inequalities for estimating the integral inequalitie...
Stochastic Processes Algorithms Time Factors Neural Networks, Computer
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Recent Advances on Dynamical Behaviors of Coupled Neural Networks With and Without Reaction-Diffusion Terms.

IEEE transactions on neural networks and learning systems Nov 30, 2020
Recently, the dynamical behaviors of coupled neural networks (CNNs) with and without reaction-diffusion terms have been widely researched due to their successful applications in different fields. This article introduces some important and interesting...
Uncertainty Fuzzy Logic Stochastic Processes Neural Networks, Computer Algorithms Feedback
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Synchronization of Coupled Time-Delay Neural Networks With Mode-Dependent Average Dwell Time Switching.

IEEE transactions on neural networks and learning systems Nov 30, 2020
In the literature, the effects of switching with average dwell time (ADT), Markovian switching, and intermittent coupling on stability and synchronization of dynamic systems have been extensively investigated. However, all of them are considered sepa...
Neural Networks, Computer Markov Chains Stochastic Processes Algorithms Probability
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Stochastic Finite-Time H State Estimation for Discrete-Time Semi-Markovian Jump Neural Networks With Time-Varying Delays.

IEEE transactions on neural networks and learning systems Nov 30, 2020
In this article, the finite-time H state estimation problem is addressed for a class of discrete-time neural networks with semi-Markovian jump parameters and time-varying delays. The focus is mainly on the design of a state estimator such that the co...
Finite Element Analysis Markov Chains Neural Networks, Computer Stochastic Processes Algorithms
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PID Controller-Based Stochastic Optimization Acceleration for Deep Neural Networks.

IEEE transactions on neural networks and learning systems Nov 30, 2020
Deep neural networks (DNNs) are widely used and demonstrated their power in many applications, such as computer vision and pattern recognition. However, the training of these networks can be time consuming. Such a problem could be alleviated by using...
Stochastic Processes Neural Networks, Computer Visual Prosthesis Deep Learning Algorithms Natural Language Processing Databases, Factual
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Measuring and Preventing COVID-19 Using the SIR Model and Machine Learning in Smart Health Care.

Journal of healthcare engineering Oct 29, 2020
COVID-19 presents an urgent global challenge because of its contagious nature, frequently changing characteristics, and the lack of a vaccine or effective medicines. A model for measuring and preventing the continued spread of COVID-19 is urgently re...
Biomedical Engineering SARS-CoV-2 Male Stochastic Processes Computer Simulation Physical Distancing Female Basic Reproduction Number Quarantine COVID-19 Saudi Arabia Disease Susceptibility Algorithms Models, Biological Forecasting Humans Delivery of Health Care Machine Learning Pandemics
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Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays.

Neural networks : the official journal of the International Neural Network Society Sep 22, 2020
This paper deals with the synchronization for discrete-time coupled neural networks (DTCNNs), in which stochastic perturbations and multiple delays are simultaneously involved. The multiple delays mean that both discrete time-varying delays and distr...
Neural Networks, Computer Time Factors Stochastic Processes
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Exponential synchronization of neural networks with time-varying delays and stochastic impulses.

Neural networks : the official journal of the International Neural Network Society Sep 19, 2020
This paper concentrates on the exponential synchronization problem of the delayed neural networks (DNNs) with stochastic impulses. First, the impulsive Halanay differential inequality is further extended to the case that the impulsive strengths are r...
Markov Chains Neural Networks, Computer Stochastic Processes Time Factors
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Stochastic DCA for minimizing a large sum of DC functions with application to multi-class logistic regression.

Neural networks : the official journal of the International Neural Network Society Sep 2, 2020
We consider the large sum of DC (Difference of Convex) functions minimization problem which appear in several different areas, especially in stochastic optimization and machine learning. Two DCA (DC Algorithm) based algorithms are proposed: stochasti...
Machine Learning Algorithms Logistic Models Stochastic Processes
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